AI Powers Faster Document Search for Nuclear Energy

Tech companies are increasingly turning to nuclear power as a reliable energy source to fuel their ambitious AI initiatives. However, nuclear power plants are notorious for slow operations and an overwhelming volume of documentation. This is where Atomic Canyon, a startup founded by Trey Lauderdale, steps in with a game-changing AI solution.

Lauderdale’s inspiration came from his hometown near the Diablo Canyon Power Plant in San Luis Obispo, California, where he noticed the plant was drowning in about 2 billion pages of documents. Recognizing the inefficiency, he envisioned AI as the key to unlocking this mountain of information for engineers, maintenance technicians, and compliance officers.

Atomic Canyon’s AI focuses on making these documents searchable using retrieval-augmented generation (RAG), a technique that combines large language models with specific document references to reduce errors known as hallucinations. This ensures users receive accurate, context-aware responses to their queries.

Early AI models struggled with nuclear-specific terminology and acronyms, but a breakthrough came after collaboration with Oak Ridge National Laboratory, which provided access to one of the world’s fastest supercomputers. This computational power enabled Atomic Canyon to train models better suited for the nuclear industry’s unique language.

Currently, Atomic Canyon’s AI enhances document search capabilities, a foundational step that minimizes risk by avoiding critical errors. Lauderdale envisions future AI applications that could draft initial versions of documents, always with human oversight to ensure safety and accuracy.

This innovative approach not only promises to accelerate nuclear plant operations but also signals a broader trend: AI’s potential to modernize and streamline heavily regulated, document-intensive industries. For nuclear power, where precision and compliance are paramount, AI-driven document management could be the catalyst for faster, safer energy production.